Papers
25
Total Citations
508
H-Index
13
About
Karel Kellens is a prominent researcher whose work spans industrial robotics, human-robot collaboration, and sustainable manufacturing. Based at the intersection of automation and practical engineering challenges, Kellens has made significant contributions to energy-efficient robot motion planning, earning 108 citations for his 2014 paper presenting a systematic, non-invasive methodology for identifying and optimizing energy consumption in industrial ABB robots — a landmark contribution to green manufacturing. His research portfolio reflects a broad curiosity: from agricultural robotics — exploring automation in apple and pear cultivation (59 citations) — to advanced grasping strategies using deep learning and vacuum grippers, and the notoriously difficult challenge of assembling non-rigid objects such as cables and foams. Kellens has also pioneered work in human-robot collaborative assembly, developing probabilistic decision models, intention estimation frameworks, and sensor-fused co-manipulation systems that allow robots to work safely and intuitively alongside humans in dynamic environments. Notably, his exploration of magnetorheological fluids in robotic grippers bridges soft robotics with the precision demands of industrial applications. With over 400 cumulative citations, Kellens has established himself as a versatile and impactful figure in intelligent automation, whose work consistently addresses real-world manufacturing and agricultural needs with innovative technical solutions.
Research Focus
Key Achievements
Top Papers
- 1Energy Efficient Trajectories for an Industrial ABB Robot108 citations · 2014
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- 5Automated assembly of non-rigid objects31 citations · 2023
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- 8Exploring the potential of magnetorheology in robotic grippers29 citations · 2018
- 9Deep Learning Reactive Robotic Grasping With a Versatile Vacuum Gripper24 citations · 2022
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